From Big data to new science and practical solutions

Projektinformationen

Data4Healthcare

ID Finanzhilfevereinbarung: 101126602

DOI

10.3030/101126602

EK-Unterschriftsdatum 18 Oktober 2023

Startdatum 1 Januar 2024

Enddatum 31 Dezember 2028

Finanziert unter

• Marie Skłodowska-Curie Actions (MSCA)

Gesamtkosten

Keine Daten

EU-Beitrag

€ 3 582 000,00

Koordiniert durch

OULUN YLIOPISTO
Finland

Periodic Reporting for period 1 - Data4Healthcare (From Big data to new science and practical solutions)

Berichtszeitraum: 2024-01-01 bis 2025-12-31

Zusammenfassung vom Kontext und den Gesamtzielen des Projekts

Data4Healthcare is a novel postdoctoral programme hosted at the University of Oulu, Finland. The programme was established to train 25 postdoctoral researchers who can work with advanced data technologies, such as big data analytics, machine vision, and artificial intelligence. In doing so, the programme aims to response a growing need: we simply do not have enough specialists who can turn today’s massive health datasets into useful knowledge that benefits people. With the help of the OuluHealth ecosystem, bringing together strong ICT know‑how, extensive molecular data, and one of the world’s most advanced digital hospital, the programme offers researchers an excellent environment to develop new solutions for future healthcare.
The programme aims to:
• Train a new generation of experts in data driven healthcare.
• Support research that contributes to better diagnostics, prevention, and wellbeing.
• Strengthen Europe’s capacity to use big data responsibly.
• Connect research with clinical and real world needs.
• Help build healthier, more resilient societies.
• Enhance international and intersectoral mobility by enabling researchers to work across countries, disciplines, and sectors

Arbeit, die ab Beginn des Projekts bis zum Ende des durch den Bericht erfassten Berichtszeitraums geleistet wurde, und die wichtigsten bis dahin erzielten Ergebnisse

The programme has successfully completed two highly competitive international recruitment rounds, which attracted strong interest from around the world. Through an open, transparent, and merit based evaluation process involving international peer reviewers, a total of 25 postdoctoral researchers were selected.
These researchers have now launched a diverse set of high‑impact projects, exploring topics such as:
• AI-assisted diagnostics and digital pathology.
• Rare-disease genetics and multi omics.
• Wearable and sensor-based health monitoring.
• Environmental and planetary health analytics.
• Data-driven public-health modeling.
Although many of the projects are still in their early phases, the fellows have already become active members of the scientific community. They have presented their work at international conferences and have contributed to the first scientific publications emerging from the programme.
To support their development, a comprehensive training curriculum has been established. All fellows are offered specialized training in responsible data use, artificial intelligence, and advanced analytics, ensuring they have the skills needed to carry out high quality research and to contribute to innovation in modern healthcare.

Fortschritte, die über den aktuellen Stand der Technik hinausgehen und voraussichtliche potenzielle Auswirkungen (einschließlich der bis dato erzielten sozioökonomischen Auswirkungen und weiter gefassten gesellschaftlichen Auswirkungen des Projekts)

The scientific and technological developments emerging from the Data4Healthcare programme have strong potential to influence the future of healthcare and wellbeing. The programme creates a clear connection between advanced data science and real clinical practice, helping to turn complex research into practical solutions. This work is already paving the way for:
• Earlier disease detection using new AI‑based digital tools
• More precise and personalised treatments through deeper insights gained from multi‑omics data
• Innovative health monitoring using wearable technologies and nanotechnology for faster diagnostics.
• Evidence-based decision-making in public health through improved environmental-health models.
As the projects progress, their outcomes may lead to new algorithms, datasets, prototypes, and health technology innovations. These could eventually be used in hospitals, clinics, public health systems, and industry. By training researchers in Open Science, intellectual property management, and innovation processes, the programme ensures that scientific discoveries do not remain in the laboratory. Instead, they can be transformed into practical tools, prototypes, and clinical solutions that bring real benefits to healthcare across Europe.